artificial neural network models of sports motions
Artificial neural network models for biomass gasification in fluidized bed gasifiers
... made in the development of these models Different kinds of models have been implemented for gasification systems, including equilibrium, kinetic and artificial neural networks According to Villanueva ... networks topology An artificial neural network is a system based on the operation of biological neural networks, a computational model inspired Fig e Relative impact (%) of input variables on ... Interpreting neural- network connection weights AI Expert 1991;6:47e51 [19] Khataee AR, Mirzajani O UV/peroxydisulfate oxidation of C I Basic Blue 3: modeling of key factors by artificial neural network Desalination...
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Báo cáo nghiên cứu khoa học: " NEURAL NETWORK CONTROL OF PNEUMATIC ARTIFICIAL MUSCLE MANIPULATOR FOR KNEE REHABILITATION" pps
... potential methods One of these novel intelligent theories includes well-known artificial neural network There are many successful commercial and industrial applications using neural network based controlling ... will take the advantage of simplicity of PID control and the neural network s powerful capability of learning, adaptability and tackling nonlinearity And the input signal of the sigmoid function ... initial values of Kp, Ki and Kd are set to be the same of the control parameters of PID controller The purpose of this experiment is to show the effectiveness of the adaptability of control parameter...
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Evolution of artificial neural network controller for a boost converter
... review of the different artificial intelligence techniques viz., Artificial Neural Networks, Particle Swarm Optimization Algorithm and Genetic Algorithms 2.1 Artificial Neural Networks Artificial neural ... e(i) Error Term in the Neural Network d(i) Desired Output of the Neural Network y(i) Actual Output of the Neural Network PWM Pulse Width Modulation xvii Chapter Introduction Artificial intelligent ... single output of the neuron appears at the axon Artificial neural networks are made up of individual models of the biological neuron connected together to form a network These neuron models are...
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ROTARY INVERTED PENDULUM AND CONTROL OF ROTARY INVERTED PENDULUM BY ARTIFICIAL NEURAL NETWORK
... model of inverted pendulum on the Simulink of Matlab in next sections III IDENTIFYING AND CONTROLLING ROTARY INVERTED PENDULUM SYSTEM BY ARTIFICIAL NEURAL NETWORK The artificial neural network ... Identifying model of pendulum system by ANN 247 Figure Result of identifying angle α by ANN and model of system with noise Table Result of identifying Form of neural Number of neunetwork rons in ... Dependence of angle α on m IV RESULTS OF EXPERIMENT The system of inverted pendulum is controlled by the ANN on the DSP TMS320F2812 with the sketch of control in Figure and the system of experiment...
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fault dialogis of spur gear box using artificial neural network
... number of epochs along with percentage efficiency of classification of various faults using ANN are computed A total The architecture of the artificial neural network is as follows: Network type No of ... such results is called neural computing or artificial neural networks ANN mimics biological neurons by simulating some of the workings of the human brain An ANN is made up of processing elements ... that when a new set of features (that is data points with unknown class values) arrive for Table Network statistics of artificial neural network for dry-No Load condition No of neurons in hidden...
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Artificial Neural Network Identification And Control Of The Inverted Pendulum
... parallelism of neural networks Artificial neural networks (ANN) have memory The memory in neural networks corresponds to the weights in the neurons Neural networks can be trained offline and ... Diagram of neuron model 18 Advantages of ANN’s The main advantage of neural networks is that it is possible to train a neural network to perform a particular function by adjusting the values of connections ... Neural Netw orks The science of artificial neural networks is based on the neuron In order to understand the structure of artificial networks, the basic elements of the neuron should be understood...
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Báo cáo khoa học: "Neural Network Recognition of Spelling Errors" docx
... beginning of words cause much greater problems than errors at the etad of words 1.1 Fixed-Length Letter Buffers The most common method of representing letters is in a buffer containing a set number of ... variables, FLLB type and local/distributed, for each of four types of error A test corpus of similarly-spelled words was developed from a list of American English homophones (Antworth 1993) Homophone ... distributed) The local method uses l of 26 nodes for each letter (total of 364 nodes), while the distributed method uses of I nodes for each letter (total of 154 nodes), with no more than two...
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a facial expression classification system integrating canny, principal component analysis and artificial neural network
... CLASSIFICATION RATE OF METHODS Method Rapid Facial Expression Classification Using Artificial Neural Networks [10] Facial Expression Classification Using Multi Artificial Neural Network [11] Classification ... Using Multi Artificial Neural Network [11] in the same JAFFE database In this paper, we suggest a new method using Canny, Principal Component Analysis (PCA) and Artificial Neural Network (ANN) ... 00 72 86 71 43 71 43 The MLP uses the algorithm of Gradient Back-Propagation for training to update W B Structure of MLP Neural Network MLP Neural Network applies for seven basic facial expression...
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facial expression classification based on multi artificial neural network
... using a Neural Network called Sub Neural Network (SNN) of MANN Lastly, we use MANN’s global frame (GF) consisting some Component Neural Network (CNN) to compose the classified result of all SNN ... of some CNN(s) The weights of CNN(s) evaluate the importance of SNN(s) like the reliability coefficients Our model links many Neural Networks together, so we call it Multi Artificial Neural Network ... L), has m Sub -Neural Network (SNN) and a global frame (GF) consisting L Component Neural Network (CNN) In particular, m is the number of feature vectors of image and L is the number of classes Definition...
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backpropagation artificial neural network in c++ - codeproject
... Neural Network Classes The neural network is composed from the following classes: ANtok Newr ANae NLyr Aern Nuo ALn Nik The A N t o k N e w r class contains the implementation of the neural network ... -esr = The minimal number of parameters to start a training session: >n1neetntokn dt1fl dt2fl 10 and.x ewr.n aa_ie aa_ie 00 It will use the network. nn file as a neural network, and load data form ... may arrange any desired Nik network structure; however, in my implementation, I provide only feed-forward full connectionist structure The basic unit of the neural network is the neuron class,...
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neural network models for formation and control
... findings of 32 the synaptic plasticity Expanding on these previous models and adaptive filter model of the cerebellum [4], we proposed a neural network model for the control of and learning of voluntary ... arms tended to minimize the following quadratic measure of performance: the integral of the square of thejerk (rate of change of acceleration) of the hand position $(x, y)$ , integrated over the ... connections The unit network consists of three layers of neurons The first layer represents the time course of the torque and the trajectory The third layer represents the change of the trajectory...
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So sánh hai mô hình dự báo tỷ suất sinh lời chứng khoán. Mô hình hồi quy truyền thống và mô hình Artificial Neural Network
... tr nên ph c t ch n lu BÁO T SU T SINH L I CH NG KHOÁN : MÔ HÌNH H I QUY TRUY N TH NG VÀ MÔ HÌNH ARTIFICIAL d báo t su t sinh l i thích h p v i t t h p lý nh a ch n mô hình u ki n c th có nh ng...
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ARTIFICIAL NEURAL NETWORK BASED DSS FOR GAME ONLINE PUBLISHING IN VIETNAM
... khe game thủ Nhu cầu khảo sát doanh nghiệp trước phát hành tựa game • Phạm vi tìm hiểu: Artificial Neural Network- based Decision Support System, Evolutionary Algorithms, thị trường game online ... ; Neural networks Ví dụ mạng dẫn tiến: Tổ chức cấu trúc mạng cụ thể: • • • Số input: Số ouput: Số nơ-ron tối đa hidden layer: 20 Giải thuật huấn luyện Thuật toán tiến hóa: Tạo quần thể mạng neural, ... http://www.gameviet24h.net, http://www.aforgenet.com/ • https://en.wikipedia.org/wiki /Artificial_ neural_ network • https://en.wikipedia.org/wiki/Evolutionary_algorithm • ANN, EA : Aforge.Net documents...
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Adaptive control and neural network control of nonlinear discrete time systems
... idea to study the computational abilities of networks composed of simple models of neurons in the 1940s [119] Neural network, like human’s brain, consists of massive simple processing units which ... determinant of matrix A the set of eigenvalues of A the maximum eigenvalue of real symmetric matrix A the minimum eigenvalue of real symmetric matrix A the absolute value of number a the index of maximum ... Background of neural network 10 1.2.2 Adaptive NN control of nonaffine systems 11 1.2.3 1.3 Adaptive Neural Network Control Adaptive NN control of multi-variable...
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Adaptive neural network control of discrete time nonlinear systems
... List of Figures ix List of Tables xii Introduction 1.1 Adaptive Neural Network Control of Nonlinear Systems 1.1.1 Neural Networks 1.1.2 Adaptive NN Control of Continuous-time ... respectively Single layer neural networks, including radial basis function (RBF) neural networks and high order neural networks (HONN), as well as multi-layer neural networks (MNN) are used Lyapunov ... Network Control of Nonlinear Systems Neural Networks Artificial neural networks (ANNs) are inspired by biological neural networks, which usually consist of a number of simple processing elements, call...
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Artificial neural network based adaptive controller for DC motors
... safeguard most Artificial neural network based adaptive controller for DC motors i Table of Contents Table of Contents Acknowledgements i Table of Contents ii Summary iv List of figures v Chapter ... based on the principle of minimization of the cost function of the error between the outputs and the target of the FFNN [4] Training of the network can be done either off-line or on-line, depending ... is generated through the off-line trainings A combination of off-line and on-line training has been used in this study The initial set of weights and Artificial neural network based adaptive controller...
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Neural network forecasts of singapore property stock returns using accounting ratios
... Appendix Neural Network Results of Capitaland 101 Appendix Neural Network Results of Hong Fok Corporation 102 Appendix Neural Network Results of Keppel Land 103 Appendix Neural Network ... Results of Bonvest Holdings 97 Appendix Neural Network Results of Bukit Semawang EST 98 Appendix Neural Network Results of Chemical INDL (FE) 99 Appendix Neural Network Results of City ... 66 4.3.1 Architecture of BP Neural Networks in Forecasting .66 4.3.2 The Model of OSL Neural Networks and Logit Neural Networks 68 4.4.3 The Monte Carlo Neural Networks 70 4.5 Summary...
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Artificial neural network modelling approach for a biomass gasification process in fixed bed gasifiers
... fraction fraction fraction of of of of carbon dioxide, – water/vapour, – methane, – tar, – Abbreviations ANFIS adaptive network- based fuzzy inference system ANN artificial neural networks C carbon CH0.83 ... Equilibrium models Stoichiometric models Non-stoichiometric models Pseudoequilibrium models Independent from gasifier type and design or specific range of operating conditions Useful in prediction of gasifier ... models and offer only static process analysis and optimisation Often, for the development of this kind of models, several assumptions have to be made Many authors analyse different kind of effects...
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Modeling the chemotaxis behaviors of c elegans using neural network from artificial to biological approach
... nervous system of animal Most of the neural network structures used presently are static (feed- Chapter Introduction forward) neural networks [28] These neural networks that have a number of neurons ... concentration of food or toxin Cmax,f Maximum concentration of food Cf Concentration of food Ctx Concentration of toxin Clef t Concentration of food or toxin on the left side Cright Concentration of food ... VC1 Voltage of CPG neuron C1 VC2 Voltage of CPG neuron C2 VC3 Voltage of CPG neuron C3 VC4 Voltage of CPG neuron C4 Llu,i Length of relaxed muscle i on left-up side Lld,i Length of relaxed muscle...
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Estimation of Proper Strain Rate in the CRSC Test Using a Artificial Neural Networks
... the reliance of the ANN Fig Flow chart for programming of the artificial neural network DESIGN ARTIFICIAL NEURAL NETWORK MODEL VERIFICATIONS OF MANN MODEL Neural networks are computer models that ... properties of the soil used for training of the MANN models are shown in Table Class Relative Importance (%) Table Properties of the soil used for learning of the MANN models Range of values Water ... rates of ANN model are more reasonable than those of other methods Preconsolidation Pressure Ratio 1.8 1.6 These limited results show the possibility of utilizing the Artificial neural network...
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